Next Article in Journal
Spatial Characteristics of the Abandonment Degree of Residential Quarters Based on Data of the Housing Sales Ratio—A Case Study of Kunming, China
Next Article in Special Issue
Automated Detection for Concrete Surface Cracks Based on Deeplabv3+ BDF
Previous Article in Journal
Deep Learning-Driven Automated Fault Detection and Diagnostics Based on a Contextual Environment: A Case Study of HVAC System
Previous Article in Special Issue
Numerical Study on Elastic Parameter Identification of Large-Span Steel Truss Structures Based on Strain Test Data
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Estimation of Soil–Structure Model Parameters for the Millikan Library Building Using a Sequential Bayesian Finite Element Model Updating Technique

1
Department of Civil and Environmental Engineering, University of Nevada, Reno, NV 89577, USA
2
Department of Civil and Environmental Engineering, University of California, Los Angeles, CA 90095, USA
3
Department of Mechanical and Civil Engineering, California Institute of Technology, Pasadena, CA 91125, USA
*
Author to whom correspondence should be addressed.
Buildings 2023, 13(1), 28; https://doi.org/10.3390/buildings13010028
Submission received: 20 November 2022 / Revised: 14 December 2022 / Accepted: 15 December 2022 / Published: 22 December 2022

Abstract

We present a finite element model updating technique for soil–structure system identification of the Millikan Library building using the seismic data recorded during the 2002 Yorba Linda earthquake. A detailed finite element (FE) model of the Millikan Library building is developed in OpenSees and updated using a sequential Bayesian estimation approach for joint parameter and input identification. A two-step system identification approach is devised. First, the fixed-base structural model is updated to estimate the structural model parameters (including effective elastic modulus of structural components, distributed floor mass, and Rayleigh damping parameters) and some uncertain components of the foundation-level motion. Then, the identified structural model is used for soil–structure model updating wherein the Rayleigh damping parameters, the stiffness and viscosity of the soil subsystem (modeled using a substructure approach), and the foundation input motions (FIMs) are estimated. The identified model parameters are compared with state-of-practice recommendations. While a specific application is made for the Millikan Library, the present work offers a framework for integrating large-scale FE models with measurement data for model inversion. By utilizing this framework for different civil structures and earthquake records, key structural model parameters can be estimated from the real-world recorded data, which can subsequently be used for assessing and improving, as necessary, state-of-the-art seismic analysis and structural modeling techniques. This paper presents an effort towards using real-world measurements for large-scale FE model updating in the soil and structure, uniform soil time domain for joint parameter and input estimation, and thus paves the way for future applications in system identification, health monitoring, and diagnosis of civil structures.
Keywords: finite element model updating; soil–structure interaction; system identification; joint system and input identification; Bayesian estimation; Millikan Library finite element model updating; soil–structure interaction; system identification; joint system and input identification; Bayesian estimation; Millikan Library

Share and Cite

MDPI and ACS Style

Ebrahimian, H.; Taha, A.; Ghahari, F.; Asimaki, D.; Taciroglu, E. Estimation of Soil–Structure Model Parameters for the Millikan Library Building Using a Sequential Bayesian Finite Element Model Updating Technique. Buildings 2023, 13, 28. https://doi.org/10.3390/buildings13010028

AMA Style

Ebrahimian H, Taha A, Ghahari F, Asimaki D, Taciroglu E. Estimation of Soil–Structure Model Parameters for the Millikan Library Building Using a Sequential Bayesian Finite Element Model Updating Technique. Buildings. 2023; 13(1):28. https://doi.org/10.3390/buildings13010028

Chicago/Turabian Style

Ebrahimian, Hamed, Abdelrahman Taha, Farid Ghahari, Domniki Asimaki, and Ertugrul Taciroglu. 2023. "Estimation of Soil–Structure Model Parameters for the Millikan Library Building Using a Sequential Bayesian Finite Element Model Updating Technique" Buildings 13, no. 1: 28. https://doi.org/10.3390/buildings13010028

APA Style

Ebrahimian, H., Taha, A., Ghahari, F., Asimaki, D., & Taciroglu, E. (2023). Estimation of Soil–Structure Model Parameters for the Millikan Library Building Using a Sequential Bayesian Finite Element Model Updating Technique. Buildings, 13(1), 28. https://doi.org/10.3390/buildings13010028

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop